Robust clustering of languages across Wikipedia growth

Abstract

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.

World influence and interactions of universities from Wikipedia networks

“…Other research groups also start to apply Wikipedia ranking in Wikiometrics [23]. We also note the growing interest to scientific analysis of several language editions of Wikipedia [24].…”

Word sense induction using word embeddings and community detection in complex networks

“…We also intend to explore the use of neural language models to generate context embeddings in order to improve the quality of the context representation. Finally, we intend to integrate our methods with other natural language processing tasks [4,5,7,14,53,49] that might benefit from representing words as context embeddings.…”

Towards a Digital Reflexive Sociology: Using Wikipedia's Biographical Repository as a Reflexive Tool

“…In recent years, information from Wikipedia has been used in various scientific disciplines, such as media studies, the geography of information, computer science, computational linguistics or social physics. It has been used to study social phenomena as diverse as the structure of relations between languages (Eom et al 2015;Ronen et al 2014;Ban, Perc, and Levnajić 2017), geopolitical instability (Apic, Betts, and Russell 2011) or the similarity of interests between countries (Karimi et al 2015). It has also been used to analyze historical processes, such as large demographic trends (Reznik and Shatalov 2016), birth-death migration trajectories (Schich et al 2014), movements of famous people during their lives (Menini et al 2017), or the influence of the media on collective memory (Jara-Figueroa, Yu, and Hidalgo 2019).…”